A current trend in environmental monitoring and surveillance is to employ multiple sensors placed at various locations in the environment. Spatial disparities of the sensors can be used to detect, localize and extract events of interest in the environment.
In order to perform these tasks accurately, the sampling of the signals needs to be synchronized. Then, any timing differences in the signals can be used to accurately pinpoint locations of sources of the signals, and to separate the signals for further processing. If the source signals are not sampled synchronously, then the time differences cannot be estimated reliably and the detection, localization and extraction of events are either grossly inaccurate or impossible.
One way to guarantee signal synchronization is to have the sampling process of all the sensors controlled by a single multi-channel sampling component. However, this method hinders an arbitrary placement of sensors, particularly where the sensors are widely dispersed in the environment and not readily accessible. Centralizing sensor control is very costly for a large number of sensors.
One method that synchronizes signals received from unsynchronized sensors uses an additional channel of input for every sensor, one for the acquired signal and one for the timing signal. This increases the cost of the system, see Lienhart et al., “On The Importance of Exact Synchronization For Distributed Audio Signal Processing,” ICASSP, April 2003.
Other methods require synchronized clocks in the various sensors, see Bletsas et al. “Natural Spontaneous Order in Wireless Sensor Networks: Time Synchronization Based On Entrainment,” to appear in Pervasive Computing, 2004. Maintaining highly synchronized clocks in many sensors is difficult and costly.
Therefore, there is a need for a cost-effective and efficient method to recover timing information from sensor signals, without requiring centralized control, additional channels, or synchronized clocks.